family factors success achievement

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Personal, family, and academic factorsaffecting low achievement in secondary school

Antonia Lozano Díaz

Teacher, Psychopegagogy expert

Almería, SPAIN

[email protected]


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Electronic Journal of Research in Educational Psychology and Psychopedagogy, 1 (1), 43 -66. ISSN: 1696-2095 - 44 -

Personal, family, and academic factors affecting low achievement in secondary school

ABSTRACT

Introduction. Understanding different parameters which contribute directly to lowachievement is a frequent topic, especially when international surveys such as the one carried

out by the OEDC show that 26% of secondary students in Spain (6% above the average of theall other countries surveyed) do not attain the corresponding diploma. The present study aimsto establish relationships between personal, family and academic factors that account forschool failure, as well as determine how these factors influence each other.

Method. The sample was composed of a total of 1178 students from four secondary schoolsin Almeria city (Spain), including the four years of Mandatory Secondary Education. In order

to collect the data two measuring instruments were used: an adaptaion of the TAMAIquestionnaire and a measurement of school failure.

Results . The results of this survey make clear the direct influence of variables such as parents'academic level, gender, motivation, relationships between peers, and others.

Discussion . The hypotheses were fulfilled differentially, showing the selective predictive

power of the different contextual variables (family and school related) in accounting forschool failure in students of Secondary Education. Such results offer us very relevantinformation for better understanding and for decision-making with an aim towards preventionof school failure during this educational stage.

KEYWORDS : school failure, secondary education, academic motivation, academicenvironment


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INTRODUCTION

Numerous studies, such as those carried out by Fullana Noel (1995) and MonteroMarcos (1990) have sought to understand the factors which account for low achievement.Studies seeking to identify what determines academic failure frequently appear as a reactionto conditions of change, such as plans for educational reform, or in response to criticalsituations: the OEDC study (2001) states that 26% of Spanish students in ESO (mandatorysecondary education) fail to obtain the corresponding diploma.

The very concept of academic failure varies in its definition. Rodríguez Castellanos(1986) considers academic failure as the situation in which the subject does not attain theexpected achievement according to his or her abilities, resulting in an altered personalitywhich affects all other aspects of life. Similarly, Tapia (2002) notes that, while the currentEducational System perceives that the student fails if he or she does not pass, moreappropriate for determining academic failure is whether the student performs below his or her potential.

In general, the various studies which attempt to explain academic failure do so

beginning with the three elements that intervene in education: parents (family causal factors),teachers (academic causal factors), and students (personal causal factors). Among personalvariables most studied are motivation and self-concept. Motivation is considered to be theelement that initiates the subject's own involvement in learning: when a student is stronglymotivated, all his effort and personality are directed toward the achievement of a specificgoal, thus bringing to bear all his or her resources. According to González (1997), aconsensus exists among the diverse motivational theories and approaches inasmuch as they

conceptualize motivation in terms of conscious beliefs and values. In the arena of motivationthere exist all kind of opinions and results, some research claims that motivation maintains acircular relationship with the level of information processing and this in turn with performance (Núñez, González-Pienda, García, González-Pumariega, Roces, Álvarez &González, 1998). In other research motivation is found to be one of the elements that mostdistinguishes those required to repeat a schoolyear from those being promoted (Burgaleta,Valverde & Fernández Garrido, 1988), the repeaters being those who are most bored in class

(Campuzano, 2001). Other authors have found that subjects themselves attribute low performance to low ability and to luck (Valle Arias et al, 1999), and an improvement in


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performance to motivation (task goal orientation), to self'-regulating behaviors, and tocompetence as a function of task characteristics (Slater, 2002). In recent research positivecorrelations were found between the value given to the task and the perceptions of auto-efficacy and performance (Yi Chia, 2002). However, in a recent theoretical review, De laFuente (2002) shows how there has been a branching off toward the study of academic goals,to the detriment of those of a social nature, even though these have been shown to beespecially important in the most disadvantaged social contexts.

Self-concept results from the subject's internalization of his social image. It isdeveloped from different interactions with the social context and agents, great importanceassigned to acceptance or rejectance from others, especially significant others. Marsh, Parkerand Smith (1983) propose a hierarchical and multifaceted model of self-concept, in whichthere exists one general factor and several specific ones, the latter including academic self-concept. For Sánchez (2000), academic self-concept is at the base of future school success orfailure, having been formed starting in Early Childhood Education from peer contact andteacher attitude and expectations. One interesting study indicates positive self-concept as onerisk-reducing factor against academic failure in the case of unfavorable family situations(Fullana Noel, 1995). Studies such as that by Castejón and Pérez (1998), using a causal-

explicative model, emphasize that academic self-concept directly influences the global performance of the pupil. Other research finds that the greater the pupil's self-concept, morelearning strategies will he use, facilitating deep information processing (Núñez Pérez et al.,1998). In other studies self-concept was found to better predict performance than variablessuch as age or student gender (Edwards, 2002). Zsolnai (2002) informed that self-conceptinfluences performance indirectly by means of its influence on intrinsic motivation. In otherresearch it was shown, by means of an analysis of structural equations, how self-concept

related causally to performance, but not vice-versa (González Pienda et al., 2002).

Another group of performance-determining factors are the social/family factors. Theeducational condition attributed to the family is beyond all doubt or discussion, as there is anever-increasing awareness of the importance of the parents' role in the progress andeducational development of their children. Schiefelbaum and Simmons (cited by Adell, 2002, p. 91) consider family background the most important and most weighty factor in determining

the academic performance attained by the student. Among family factors of greatestinfluence are social class variables and the educational and family environment.


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With regard to social class, relevant research tells us that one's results and expectationsfor the future are better the higher one belongs on the social ladder. One of the latest studiescarried out on performance in secondary school in Spain (Marchesi and Martín, 2002),informed that upper-class students show a better use of metacognitive strategies than those ofa lower social class. The influence of social class is mediated by cultural level, which in turndetermines family expectations, values and attitudes regarding education. In other words,motivation to achieve depends more on the parents' level of learning than on their level ofincome (Llorente Guardione, 1990). Castejón and Pérez (1998) find that the child's perceptionof family support directly affects performance, while the mother's level of studies does soindirectly. Other research indicates that the most influential family components on performance are not socio-cultural or economic, but rather those pertaining to the affective or psychological dimension; that is, although good academic preparation in the parents,especially the mother, and a positive cultural environment, favor scholastic performance, it isaffective and relational variables which most stand out as factors in performance.

The influence of the family educational climate is defined by the amount and the styleof help that children receive from the family; this is determined by elements of the familycontext, like the dynamic of communication and affective relationships, attitudes towards

values, expectations, etc. Along these same lines, Marchesi and Martín (2002) tell us that parental expectations have a notable influence on academic results, even when controlling forinitial knowledge and socio-economic context. Castejón and Pérez (1998) find indirectrelationships with performance from the student's perception of how much importance his orher parents assign to study at home. Other studies show that the level of family cohesion(Caplan et al, 2002) and family relationships (Buote, 2001) prove themselves capable of predicting performance. The parenting style (democratic, authoritarian, etc) is also influential

both in the students' educational process as well as in family-school relations; research such asthat by Rodríguez Castellano (1986) demonstrate that a positive family climate favors thedevelopment of well-adapted, mature, stable and integrated subjects, and an unfavorablefamily climate promotes non-adaptation, immaturity, lack of balance and insecurity.

The last group of determining factors is made up of school variables, principally thestudent's teacher and his peers. Marchesi and Martín (2002) propose that the pupil's

sociocultural level and his previous aptitudes indirectly influence the results of learning sincethey delimit classroom procedures. As for characteristics of the teacher-tutor, this is


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considered a key element for the pupil's personal and academic development, the value givenfrom teacher to pupil and vice-versa are usually reciprocal, highlighting additionally the personal relationship (Marchesi and Martín, 2002). These same authors find that teacherexpectations significantly influence student results. The teachers' assessment is mediated bytwo variables: (1) the student's intelligence, that is, the greater the intelligence, the better theacademic results and the better reciprocal appreciation between teacher and student; (2)family support for study also makes the student value his teacher more highly (Castejón andPérez, 1998). Other studies find positive relationships between the teacher's motivation andthat of the student (Atkinson, 2000). Teacher-pupil relations are also mediated by theteacher's attribution of poor performance to the student (Georgiou et al., 2002). Peerinfluence on the child's development occurs by similar mechanisms as those used by adults:reinforcement, modeling, and direct teaching and skills. Interaction with peers also promotesacquisition of social competencies such as controlling aggressive impulses and the expressionof prosocial behaviors. In relation to academic performance, the sociometric status of thestudent influences performance both directly and indirectly, since it is influenced byintelligence (Castejón & Pérez, 1998). Other research also shows that positive correlationsexist between performance and peer relationships (Buote, 2002), demonstrating in anotherstudy that students failing in school are those most rejected by their group-class (Montero,

1990).Objectives

The general objective of our own research was to find evidence of the influence of aset of diverse variables on school failure. We believe that the results allow us to more sharplyfocus data obtained in other studies regarding school failure which only take into account oneof the different variables involved (Burgaleta et al, 1988; Valle Arias et al, 1999; Sánchez,2000; Buote, 2001; Caplan et al, 2002, among others), this is especially important if we wish

to have a more complete view of the multiple causes that, interactively, produce results ofschool failure and/or low performance. For more specific objectives, we proposed thefollowing: (1) see to what extent the different variables are interrelated and influence andexplain scholastic failures; (2) try to establish the differential incidence that each variable may present on scholastic failure.

Hypotheses

H1: personal variables (age), academic variables (grade level) and family variables(parents' level of education) together with affective-motivational variables


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(questionnaire variables), taken jointly, must be able to predict school failure to agreater extent than they can individually.H2: personal variables (age), academic variables (grade level) and family variables(parents' level of education) must be able to predict the affective-motivational level ofthe student.H3: personal variables (gender and age), family variables (mother and father's level ofeducation) and academic variables (secondary school, group, and cycle) must affectthe student's academic performance as well as his affective-motivational level.H4: the affective-motivational variables should affect the level of student performance.

METHOD

Subjects

The sample was made up of a total of 1178 students from four secondary schools inAlmeria city, representing in turn the four grade levels of Mandatory Secondary Education(E.S.O.). The students' distribution is as follows: 255 subjects from first year, 316 fromsecond year, 296 from third year, and 259 from fourth. As for gender, 565 were girls, and 603 boys. The average age was 13.73 years (sd=1.41). Students were divided into groups as

follows: group A, 403 students; group B, 364; group C, 310; group D, 84; group E, 17students.

Instruments

In order to perform data collection two measuring instruments were used: anadaptation of the TAMAI questionnaire, and a measure of scholastic failure.

1) Measure of personal, family and personal adaptation.The “Self-assessing Multifactorial Test of Childhood Adaptation” TAMAI

(Hernández & Hernández, 1998), was used to evaluate the student's level of personal, social,academic and family adaptation, as well as parents' attitudes in childraising. It consists of aself-assessment containing 175 propositions to which one must respond affirmatively ornegatively; the excessive number of items and the characteristics of the sample required anadaptation of the questionnaire. We selected a total of 34 items from the original test, which,when submitted to an Alpha of Cronbach reliability analysis produced a resulting index of.72, acceptable enough. Subsequently, we carried out an exploratory factorial analysis of 34


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items in order to facilitate organization and comprehension of the information we wereaiming to collect. In order to determine whether the factorial analysis was adequate or not,we previously carried out Bartlett's Test of Sphericalness (in order to sustain that in effectthere did exist significant intercorrelations between the items) and the Kaiser-Meyer-Olkinindex (measure of sample adequacy). The values of both, which should be as high as possible,were as follows for each level of analysis; level 1 (12 factors) KMO= .761; Barlett= 3362;signif. = .000; level 2 (four dimensions) KMO= .744; Barlett= 929.598; signif.= .000; level 3(one component) KMO= .609; Barlett= 211.07; signif.= .000.

The adapted questionnnaire was named “Questionnaire on motivational, affective andsocial/family aspects in the academic environment”. Its organization and structure is asfollows:

Dimension 1. Academic environment.Factor 2: Academic self-concept.Factor 3: Relationships with parents and adults.Factor 4: Social relationships in class.Factor 6: Friendship relations.

Factor 12: Locus of control.Dimension 2. Academic motivation.

Factor 1: Behavior in class.Factor 8: Future expectations.

Dimension 3. Social support.Factor 5: Family interest.Factor 7: Perceived acceptance.

Factor 11: Relationship with teachers.Dimension 4. Academic and affective assessment.

Factor 9: Academic assessment.Factor 10: Affective assessment.

2) Measure of academic failure.The number of schoolyears repeated was used as a criterion, classified thus: 0

schoolyears repeated, 1 schoolyear repeated, 2 schoolyears repeated.


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Design The different sections of the questionnaire constitute what we will callquestionnaire

variables , and take in personal, family and academic variables. The remaining variables wereconsidered selection variables , and also take in personal, family and academic variables: thenumber of years repeated, the grade level, the secondary school and the group (academicvariables), age and gender (personal variables), mother and father's educational level (familyvariables). Thus we have two types of variables, selection and questionnaire , even though both allude to: personal variables (age, gender, academic self-concept, locus of control,classroom behavior, perceived acceptance, affective assessment), family variables (parents'educational level, relationships with parents and adults, family interest), andacademicvariables (number of schoolyears repeated, grade level, secondary school, group socialrelationships in class, friendship relations, future expectations, relationships with teachers,academic assessment).

Procedure

Questionnaires were completed in the classroom, during normal class hours,administered by the guidance counselor at each secondary school, and in an entirelyanonymous fashion for each student. In order to demonstrate the first two hypotheses, a

multiple regression analysis was carried out, while for the remaining hypotheses a simpleanalysis of variance (ANOVA) and a multiple analysis of variance (MANOVA) were carriedout.

RESULTS

Predictive relationships

In Tables 1, 2 we find the results of the regression analysis used for the purpose of

satisfying this investigation's first objective. In Table 1, one can observe the power for predicting academic failure by means of the variables grade level, age, father and mother's studies ; the indexes show that all variables exceptmother's studies , are able to rathersignificantly predict performance, although in a different was as shown by the beta index.Thus we find that the grade level and the father's level of studies negatively predict thenumber of schoolyears repeated, whileage does so such that the greater the age, the greaterthe number of schoolyears repeated. In Table 1 we also ascertain (in another regression

analysis independent from the earlier one) how affective-motivational aspects predictacademic failure; only two of the four dimensions show predictive character, and that of a


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negative sense, that it, the greater the number of grades repeated, the lower score is shown in Academic and Academic motivation

TABLE 1Regression analysis between academic variables (grade level), personal variables (age) andfamily variables (father's and mother's studies) and the number of schoolyears repeated, and

between the affective-motivational variables and the number of schoolyears repeated.

predictivevariable

CriterionVariable

F p< Beta

Grade levelAgeFather's studiesMother's studies

Schoolyearsrepeated

296.44****-1.082***1.482***-0.079**-0.013

D1. Academic environmentD2. Academic motivationD3. Social supportD3. Academic and affective

assessment

Schoolyearsrepeated

11.098**-0.150***-0.105**0.0000.009

*p


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TABLE 2Joint regression analysis between personal variables (age), academic variables (grade level),

family variables (father's level of studies) and affective-motivational variables andschoolyears repeated.

predictingvariable Criterionvariable F p< Beta p< R correctedsquare

Schoolyearsrepeated

333.67****-1.100***1.506***-0.062**-0.060**

0.582 =34%

*p


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TABLE 4Simple analysis of variance (anova) and multiple analysis of variance (manova) between age

and gender and schoolyears repeated and the affective-motivational variables.

Factor indexes F p< dependent variable F p<

AGE:

GENDER

ANOVA :

MANOVA:Pillais

ANOVA:

3.12***

Schoolyears repeated1) 11-14 M=0,13 (sd= 0.38)2) 15-18 M=0,65 (sd= 0.71)

Academic environmentAcademic motivationSocial supportAcademic and affective

assessmentSchoolyears repeated1) Male M= 0.34 (sd=0.63)2) Female M= 0.23 (sd=0.48)

263.05****( 2>1 )

2.44**3.89***4.91***1.98

14.89***( 1>2 )

*p


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TABLE 5

Simple analysis of variance (anova) and multiple analysis of variance (manova) between thefather's and mother's level of studies and schoolyears repeated

and the affective-motivational level.factor indices F

p<dependent variable F p<

FATHER'SSTUDIES:

MOTHER'SSTUDIES:

FATHER'SSTUDIES xMOTHER'SSTUDIES:

ANOVA:

MANOVA:

Pillais

MANOVA :Pillais

MANOVA:Pillais

1.52

1.87*

1.23

Schoolyears repeated1) Does not read/write M= 0.722) Primary Studies M= 0.303) Secondary Studies M= 0.134) Higher Education M= 0.13

Academic environmentAcademic motivationSocial supportAcademic and affectiveassessment



3.454*(1>2>3, 4 )

2.283.98**0.290.67

0.694.80**0.601.02

0.,871.95*1.380.95

*p


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ability for variation in performance, F(1.149)=19.261,pC>B>A. Once again we find that for diverse reasons(choice of electives is the most usual) students are grouped according to their performance; itdoes not show, however, significant differences in the manova for any of the four affective-motivational dimensions. The factorcycle , just as one might expect, yields differences in theanova, F(1.149)=24.875, p


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TABLE 6Simple analysis of variance (anova) and multiple analysis of variance (manova) between

academic factors and schoolyears repeated and the affective-motivational level.

Factor indices F p< dependent variable F p<

SecondarySchool:

Group:

Cycle:

School xGroup

School xCycle

ANOVA:

MANOVA:Pillais

ANOVA:

ANOVA:

ANOVA

ANOVA

MANOVAPillais

2,72**

1.98*

Schoolyears repeated 4.883**School1 M=0.27 (sd=0.55) ( 4>2>1>3 ) School2 M=0.29 (sd=0.57)School3 M=0.22 (sd=0.47)School4 M=0.37(sd=0.64)

Academic environment 0.53Academic motivation 1.27Social support 2.41Academic and affective 5.23**assessment

Schoolyears repeated 19.261****Group A M= 0.16 (sd=0.44)Group B M= 0.26 (sd=0.52)( D>C>B >A) Group C M= 0.36 (sd=0,62)Group D M= 0.67 (sd=0,71)

Schoolyears repeated 24.875****Cycle 1 M= 0.18 (sd= 0.47)Cycle 2 M= 0.39 (sd= 0.62)

Schoolyears repeated 5.081***School1, Gr. A M=0.26 (sd=0.12)School2, Gr. A M=0.21 (sd=0.52)(4>1>2>3)School3, Gr. A M=0.08 (sd=0.33)School4, Gr. A M=0.38 (sd=0.61)

Schoolyears repeated 3.996**School1 Cycle 1 M=0.15 (sd=0.41)

Cycle 2 M=0.4 (sd=0.6)School2 Cycle 1 M=0.21 (0.49)Cycle 2 M=0.38 (0.63)

( 1>4>2>3)School3 Cycle 1 M=0.17 (0.39)

Cycle 2 M=0.28 (0.53)School4 Cycle 1 M=0.22 (0.62)

Cycle 2 M=0.49 (0.62)

Academic environment 0.69Academic motivation 0.77

Social support 2.52Academic and affective assessment 3.93**


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School xGroup xCycle

ANOVA:

MANOVA:PillaisWilksHotelling

2.57***2.57***2.57***

Schoolyears repeated 4.883***School1 Gr. A Cycle 1 M= 0.00 (sd=0.00)

Cycle 2 M= 0.03 (sd = 0.18)

Gr. D Cycle 1 M= 0.62 (sd = 0.63)Cycle 2 M= 1.33 (sd = 0.81)School2 Gr. A Cycle 1 M= 0.17 (sd = 0.49)

Cycle 2 M= 0.24 (sd = 0.54)Gr. C Cycle 1 M= 0.27 (sd = 0.49)

Cycle 2 M= 0.20 (sd = 0.41)School3 Gr. A Cycle 1 M= 0.06 (sd = 0.31)

Cycle 2 M= 0.10 (sd = 0.36)Gr. C Cycle 1 M= 0.25 (sd = 0.43)

Cycle 2 M= 0.35 (sd = 0.62)School4 Gr. A Cycle 1 M= 0.16 (dt= 0.48)

Cycle 2 M= 0.58 (dt= 0.65)Gr. C Cycle 1 M= 0.46 (dt= 1.06)

Cycle 2 M= 0.50 (dt= 0.60)

Academic environment 3.87***Academic motivation 1.59Social support 1.08Academic and affective 4.07***assessment

*p


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those with most academic failure. The variables ofSocial support and Academic andaffective assessment do not present enough explicative ability for the variation in performance.

TABLE 7Simple analysis of variance (anova) between affective-motivational aspects

and schoolyears repeated.

Dependent variable F p< independent variable

D1. ACADEMICENVIRONMENT

D2. ACADEMICMOTIVATION

D3. SOCIALSUPPORT

D4. ACADEMIC ANDAFFECTIVE

ASSESSMENT

1.54***

5.65***

0.90

0.52

Schoolyears repeated0 years M= 1.79 (sd= 0.15) (0>1>2)1 year M= 1.71 (sd = 0.16)2 years M= 1.65 (sd = 0.10)

Schoolyears repeated0 years M= 1.76 (sd = 0.22) (0>1,2)1 year M= 1.67 (sd = 0.27)2 years M= 1.67 (sd = 0.23)

Schoolyears repeated0 years M= 1.76 (sd = 0.17) (0>1,2)1 year M= 1.73 (sd = 0.61)2 years M= 1.73 (sd = 0.14)

Schoolyears repeated0 years M= 1.83 (sd = 0.23) (0>2>1)1 year M= 1.80 (sd = 0.21)2 years M= 1.82 (sd = 0.20)

*p


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we construct a model with the variables that, in an interactive fashion, are able to explain asmuch as 34% of the variance of performance: personal determinants such asage , academic

self-concept (factor 2) and the Locus of control (factor 12); family determinants such as thelevel of Father's studies and the Relationship with parents and adults (factor 3) and academicdeterminants such as grade level , Friendship relationships (factor 6) andSocial relationshipsin class (factor 4). These results concur with those found in diverse research efforts (Fullana,1995; Llorente, 1990; Martínez, 1996; Montero, 1990; Valle Arias et al, 1999)

In order to finish addressing the first objective of our research, we inquired as to howthe different variables interacted among themselves such as was proposed in the secondhypothesis. The affective-motivational variable best explained by the regressors (consideredas a whole, not individually) is Academic environment, which maintains a positiverelationship with father's studies and grade level and a negative one withage , that is, it is therepeating students (who obviously are getting older) who maintain a low score in thisdimension. Academic motivation is also explained negatively fromage but not from gradelevel , implying again that this negative relationship is due to the students who show mostfailure (similar results found by Burgaleta et al, 1988). As students progress to higher gradelevel they also claim to perceive lessSocial support , this may be due to teachers and parents

who withdraw once they see the student is getting on well, or it may be due to the student's being written off as “hopeless” given his bad performance. Academic and affectiveassessment is the second best explained dimension by two of the regressors, grade level and

mother's studies : as these two variables increase, the students feel more concerned about notdispleasing those who they appreciate, they blame themselves more for the negative aspectsof their life, and feel that their future depends less on their studies.

The anova and manova carried out later allowed us to address our second researchobjective, as well as the third and fourth hypotheses. The anova with the factorage showedthe expected effect that the older students show the highest failure index (there are morerepeaters as age increases); the manova on affective-motivational aspects verifies theexplicative ability ofage in the variation of scores for Academic environment , Academicmotivation, and Social support . With relation to gender , the fact is clear that women perform better than men, although this factor does not differentially influence the variance of

affective-motivational factors.


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The analysis of variance carried out with the level of father's and mother's studiessharpens the results obtained with the regression analysis. Again the level of father's studies is able to explain the variation in performance and in Academic motivation , while the level ofmother's studies is only able to explain the variation in Academic motivation (although moresignificantly than the father's studies). This factor indirectly influences performance by meansof Academic motivation that, as we recall, was the affective-motivation variable with thegreatest predictive power for performance. In fact, the joint level of studies of the father andthe mother does not directly explain performance, but they do so through the level of

Academic motivation of their child, results concurring with those found by Llorente (1990).

The analysis of variance on the factorsSecondary school and group and cycle, showdifferent levels of interaction with performance and the affective-motivational aspects. Withregard to Secondary School a significantly lower performance appears in one of the schools,which is, additionally, the only one that also presents significant variation in Academic andaffective assessment . The fact that the school's students with lowest performance are thosethat score most highly in this affective-motivational dimension, leads one to think that such anassessment may be the result of academic failure. To begin with, this variable showed littleexplicative ability for performance.

The last anova carried out allowed us to partially confirm the paper's last hypothesis.The variable with the most explicative ability of the performance variance is Academicmotivation , whose level decreases as performance decreases (similar results obtained byRoces, Touron & González, 1995; Campuzano, 2001; Checa, 2000). Motivation alsodecreases with age, although more slowly if performance is good. Academic environment , aswe have already seen, also shows explicative ability, in the same direction, for performance.

The dimensions of Academic and affective assessment and Social support do not explain performance, rather they appear to be a consequence of low performance.

In spite of results and evidence found, this research also presents limitations which itis necessary to mention. One of the main limitations or lacks is the absence of greatercontextualization for each of the schools, and above all, of the origin of its student body,making possible better information about socio-economic and cultural factors, of no small

importance when it comes to better understanding the influence of the environment inacademic failure. In addition to the outside context, it would be fundamental to have


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information about the specific context of each school and class. Another important lack isseen in the absence of information from more qualitative techniques to triangulate the resultsfound.

Keeping all this in mind, and in concordance with the limitations exposed and theresults obtained, future lines of research should explore more deeply and more specifically theway in which variables like the type of goals pursued by the student, his or her personalitycharacteristics, class organization, peer group pressure, teacher personality and style, etc.influence the evolution and type of affective-motivational characteristics that the students areacquiring throughout their journey through the Educational System, and the repercussions ofall that in the student's final performance, and therefore in his or her potential academicfailure.

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